| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 1312 | 2024 |
| Practical deep learning with Bayesian principles K Osawa, S Swaroop, MEE Khan, A Jain, R Eschenhagen, RE Turner, ... Advances in neural information processing systems 32, 2019 | 308 | 2019 |
| Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks K Osawa, Y Tsuji, Y Ueno, A Naruse, R Yokota, S Matsuoka The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp …, 2019 | 161* | 2019 |
| Scalable and practical natural gradient for large-scale deep learning K Osawa, Y Tsuji, Y Ueno, A Naruse, CS Foo, R Yokota IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (1), 404-415, 2020 | 43 | 2020 |
| Efficient quantized sparse matrix operations on tensor cores S Li, K Osawa, T Hoefler SC22: International Conference for High Performance Computing, Networking …, 2022 | 41 | 2022 |
| Understanding approximate fisher information for fast convergence of natural gradient descent in wide neural networks R Karakida, K Osawa Advances in neural information processing systems 33, 10891-10901, 2020 | 37 | 2020 |
| Accelerating matrix multiplication in deep learning by using low-rank approximation K Osawa, A Sekiya, H Naganuma, R Yokota 2017 International Conference on High Performance Computing & Simulation …, 2017 | 27 | 2017 |
| PipeFisher: Efficient training of large language models using pipelining and Fisher information matrices K Osawa, S Li, T Hoefler Proceedings of Machine Learning and Systems 5, 708-727, 2023 | 25 | 2023 |
| Neural graph databases M Besta, P Iff, F Scheidl, K Osawa, N Dryden, M Podstawski, T Chen, ... Learning on Graphs Conference, 31: 1-31: 38, 2022 | 21 | 2022 |
| Rich information is affordable: A systematic performance analysis of second-order optimization using K-FAC Y Ueno, K Osawa, Y Tsuji, A Naruse, R Yokota Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 20 | 2020 |
| Understanding gradient regularization in deep learning: Efficient finite-difference computation and implicit bias R Karakida, T Takase, T Hayase, K Osawa International Conference on Machine Learning, 15809-15827, 2023 | 13 | 2023 |
| Asdl: A unified interface for gradient preconditioning in pytorch K Osawa, S Ishikawa, R Yokota, S Li, T Hoefler arXiv preprint arXiv:2305.04684, 2023 | 12 | 2023 |
| Performance optimizations and analysis of distributed deep learning with approximated second-order optimization method Y Tsuji, K Osawa, Y Ueno, A Naruse, R Yokota, S Matsuoka Workshop Proceedings of the 48th International Conference on Parallel …, 2019 | 7 | 2019 |
| Second-order optimization method for large mini-batch: training resnet-50 on imagenet in 35 epochs (2018) K Osawa, Y Tsuji, Y Ueno, A Naruse, R Yokota, S Matsuoka arXiv preprint arXiv:1811.12019, 2018 | 5 | 2018 |
| Evaluating the compression efficiency of the filters in convolutional neural networks K Osawa, R Yokota Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017 | 4 | 2017 |
| Improving continual learning by accurate gradient reconstructions of the past E Daxberger, S Swaroop, K Osawa, R Yokota, RE Turner, ... Transactions on Machine Learning Research, 2023 | 3 | 2023 |
| Efficient cluster mapping for conditions of weather based on combination of self-organizing map and hierarchical clustering K Osawa, K Kamei, M Ishikawa IEICE Technical Report; IEICE Tech. Rep. 119 (453), 213-218, 2020 | 2 | 2020 |
| Accelerating Convolutional Neural Networks Using Low-Rank Tensor Decomposition K Osawa, A Sekiya, H Naganuma, R Yokota IEICE Technical Report; IEICE Tech. Rep. 117 (238), 1-6, 2017 | | 2017 |
| Examination about the salt solution filling packing method of sea urchin (Strongylocentrotus nudus) gonad K Osawa, Y Kado, N Notoya, M Koizumi, S Ishikawa Report of Aomori Prefectural Local Food Research Center (Japan), 2004 | | 2004 |
| Research and development of new processed foods M Koizumi, S Ishikawa, N Notoya, Y Kado, K Osawa Report of Aomori Prefectural Local Food Research Center (Japan), 2004 | | 2004 |
Mohammad Emtiyaz KhanCenter for Advanced Intelligence Project (AIP), RIKEN, TokyoVerified email at postman.riken.jp
